Arbeitspapier
Joint Bayesian Analysis of Parameters and States in Nonlinear, Non-Gaussian State Space Models
We propose a new methodology for designing flexible proposal densities for the joint posterior density of parameters and states in a nonlinear non-Gaussian state space model. We show that a highly efficient Bayesian procedure emerges when these proposal densities are used in an independent Metropolis-Hastings algorithm. A particular feature of our approach is that smoothed estimates of the states and the marginal likelihood are obtained directly as an output of the algorithm. Our method provides a computationally efficient alternative to several recently proposed algorithms. We present extensive simulation evidence for stochastic volatility and stochastic intensity models. For our empirical study, we analyse the performance of our method for stock returns and corporate default panel data. (This paper is an updated version of the paper that appeared earlier as Barra, I., Hoogerheide, L.F., Koopman, S.J., and Lucas, A. (2013) "Joint Independent Metropolis-Hastings Methods for Nonlinear Non-Gaussian State Space Models". TI Discussion Paper 13-050/III. Amsterdam: Tinbergen Institute.)
- Language
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Englisch
- Bibliographic citation
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Series: Tinbergen Institute Discussion Paper ; No. 14-118/III
- Classification
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Wirtschaft
Bayesian Analysis: General
Statistical Simulation Methods: General
Single Equation Models; Single Variables: Time-Series Models; Dynamic Quantile Regressions; Dynamic Treatment Effect Models; Diffusion Processes
Multiple or Simultaneous Equation Models: Time-Series Models; Dynamic Quantile Regressions; Dynamic Treatment Effect Models; Diffusion Processes; State Space Models
Financial Econometrics
- Subject
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Bayesian inference
importance sampling
Monte Carlo estimation
Metropolis-Hastings algorithm
mixture of Student's t-distributions
- Event
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Geistige Schöpfung
- (who)
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Barra, István
Hoogerheide, Lennart
Koopman, Siem Jan
Lucas, André
- Event
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Veröffentlichung
- (who)
-
Tinbergen Institute
- (where)
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Amsterdam and Rotterdam
- (when)
-
2014
- Handle
- Last update
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10.03.2025, 11:41 AM CET
Data provider
ZBW - Deutsche Zentralbibliothek für Wirtschaftswissenschaften - Leibniz-Informationszentrum Wirtschaft. If you have any questions about the object, please contact the data provider.
Object type
- Arbeitspapier
Associated
- Barra, István
- Hoogerheide, Lennart
- Koopman, Siem Jan
- Lucas, André
- Tinbergen Institute
Time of origin
- 2014
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Bayesian Risk Forecasting for Long Horizons
Beta observation-driven models with exogenous regressors: a joint analysis of realized correlation and leverage effects
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A Dynamic Yield Curve Model with Stochastic Volatility and Non-Gaussian Interactions: An Empirical Study of Non-standard Monetary Policy in the Euro Area
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A Dynamic Bivariate Poisson Model for Analysing and Forecasting Match Results in the English Premier League
The dynamic factor network model with an application to global credit risk
Joint Independent Metropolis-Hastings Methods for Nonlinear Non-Gaussian State Space Models
Numerically Accelerated Importance Sampling for Nonlinear Non-Gaussian State Space Models
Bayesian Dynamic Modeling of High-Frequency Integer Price Changes
Bayesian Risk Forecasting for Long Horizons
Beta observation-driven models with exogenous regressors: a joint analysis of realized correlation and leverage effects
A Non-Gaussian Panel Time Series Model for Estimating and Decomposing Default Risk
Optimal Formulations for Nonlinear Autoregressive Processes
A Dynamic Yield Curve Model with Stochastic Volatility and Non-Gaussian Interactions: An Empirical Study of Non-standard Monetary Policy in the Euro Area
Joint Modelling and Estimation of Global and Local Cross-Sectional Dependence in Large Panels
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